Stem cell secretome-treatment improves whole-body metabolism, reduces adiposity and promotes skeletal muscle function in aged mice
RNA-seq (gene expression) · mouse · 20 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Mus musculus (mouse)
- Samples
- 20 samples: 20 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Stem cell secretome treatment improves whole-body metabolism, reduces adiposity, and promotes skeletal muscle function in aged miceAging cell · 2024
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE242211_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1011995 and SRA study SRP458090. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 20 sample titles: 20 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM7755640 20233X1 Control 1
- GSM7755641 20233X2 Control 2
- GSM7755642 20233X3 Control 3
- GSM7755643 20233X4 Control 4
- GSM7755644 20233X5 Control 5
- GSM7755645 20233X6 Control 6
- GSM7755646 20233X7 Control 7
- GSM7755647 20233X8 Control 8
- GSM7755648 20233X9 Control 9
- GSM7755649 20233X10 Control 10
- GSM7755650 20233X11 Secretome 1
- GSM7755651 20233X12 Secretome 2
- GSM7755652 20233X13 Secretome 3
- GSM7755653 20233X14 Secretome 4
- GSM7755654 20233X15 Secretome 5
- GSM7755655 20233X16 Secretome 6
- GSM7755656 20233X17 Secretome 7
- GSM7755657 20233X18 Secretome 8
- GSM7755658 20233X19 Secretome 9
- GSM7755659 20233X20 Secretome 10
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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.